Last month General Mills announced to Trix’s die-hard fans that it would return to artificial dyes and flavors, after two years and a lukewarm consumer reception to natural colorings from turmeric, strawberries and radishes. Turns out consumers far preferred Red #40, Yellow #6 and Blue #1 dyes.

For some time now, the healthcare industry has known that social determinants (items like food quality, residential address, access to education, etc) play a significant role in one’s health but the industry has struggled to properly assess, much less manage, such important factors. Coincident with this, my focus for some time has been about how close we are to actually developing tools to effectively accomplish this.

The premise is that multiplexing a set of disparate data sets will provide some startling (and hopefully actionable) insights. For instance, one question we should be close to answering is “what is the quality of caloric consumption by a specific address, and maybe by each individual at that address?” Census data and voting rolls tell us how many people live at any specific address and their ages. Credit card and other loyalty purchasing programs can provide food purchases by SKU. Other data sets such as medical data, FICO, social media consumption and utility records, when overlaid on top of each other, will provide even more insights as to what happens at that address.

With some fanfare, the Federal Reserve recently announced that U.S. household net worth reached $96.2 trillion at the end of 2Q17 and that the ratio of wealth to income was 670%. Notwithstanding that, economists at Merrill Lynch are worried about tepid consumer spending given that according to their estimates, for every dollar increase in household net worth, consumers only spent $0.02. Ten years ago, pre-Great Recession, total net worth was $68.2 trillion which suggests that a significant amount of the improvement was not cycled into the economy.

But to return to the question at the outset. The Bureau of Labor Statistics (BLS) is a treasure trove of data which gets closer to some answers. At the end of 2016, average household income was $59,039 which was an increase of 3.2% from 2015 (and 2015 was an increase of 5.2% from 2014 levels). But averages can be misleading: the 90th percentile had $170,000 of household income while the 10th percentile earned $13,600 – clearly underscoring the dramatic income inequality gap in this country. Interestingly, the top 20% took home 51% of total income. The U.S. poverty rate at the end of 2016 was 12.7% and represented 40.6 million Americans.

The 90th percentile spent 10.7% of its income on food while the 10th percentile spent 16.1% of its income on food; not terribly surprising given the relatively fixed cost nature of food. According to the USDA, the average middle aged male needs 2,600 calories per day while a female of comparable age requires 2,000 daily calories. Interestingly, if that same male only eats 1,861 calories, he will lose one pound per week. Fortunately, the BLS also breaks down the type of food each percentile purchases, which is where one begins to see some striking differences in the types of calories purchased. Consistently, across the 20 food categories tracked, more processed foods (sugars, fats, etc) were purchased by the 10th percentile than the 90th percentile (fats: 1.9% vs 1.3%, respectively) as a percent of overall household expenditures.

It is quite clear that inexpensive, more processed (relatively unhealthy) food is more readily available and accessible today. Arguably healthy, more expensive food will show great price elasticity; that is, increases in healthy food price will lead consumers to purchase less expensive unhealthier foods. Notably, the average U.S. household spent 9.7% of its annual income in 2016 on food and only 6.2% on healthcare (and 25.3% on housing). As important as the healthcare expenditures are, the “non-healthcare” categories play a material role in one’s health. Globally, the New England Journal of Medicine estimates that there are 700 million obese people, 108 million of which are children. That is, 10% of the world’s population has Body Mass Index (BMI) greater than 30 which is considered obese (dare you to click on that link…). The New York Times recently profiled a multinational processed food company which had developed a sophisticated door-to-door distribution network in Brazil and the resultant increased incidence of associated chronic diseases.

Last week PepsiCo announced 3Q17 results which showed a 3% decline in revenues and a 10% decrease in earnings, which the CFO attributed to efforts to diversify away from sugary drinks and their “multi-year journey to move to healthier products.” Just last week, Kellogg acquired the protein bar manufacturer Rixbar for $600 million to strengthen its healthy products business unit. So far in 2017, the CEOs of the five largest food companies have been replaced as the food industry struggles to find sustainable growth strategies.

Unfortunately, all of this brings back difficult childhood memories from when my friends wanted to get under my skin and chanted “Let’s get Mikey…he won’t eat it…he hates everything” (although I still very much like Life cereal).

U.S. consumer product companies are the most powerful force for behavior change in the world. “Engaged health” consumers pay a premium for the perceived value of “healthy” products (Nike, Fitbit, Whole Foods, etc.) but as you point out the most challenged among us continue to buy cheap calories. And then there is the cultural resistance to healthy eating recommendations.

Is it possible processed foods are bought because people don’t know how to cook? As a European import, I see this all the time, with great shock, including in my 1-10th percentile friends. Regardless, animals love fat, sugar and salt, an innate trait that is hard to beat, unfortunately, and food companies bank on. Great piece, thanks.